AWS Certified Generative AI Developer - Professional (AIP-C01) Practice Tests

Use this AIP-C01 practice exam to prepare for AWS Certified Generative AI Developer - Professional (AIP-C01) with realistic questions, detailed explanations, and focused study modes. The practice bank includes 1,978 questions for AWS AIP-C01, so you can review the exam steadily instead of relying on one long cram session.

As you practice, pay extra attention to recurring topics such as Foundation Model Integration, Data Management and Compliance, Implementation and Integration, AI Safety and Security, and Operational Efficiency. Start with short sessions to identify weak areas, then move into timed quizzes once your accuracy is consistent.

The explanations are especially useful when you want to connect exam wording to the responsibilities and scenarios described in the official certification guidance. Use the free preview first, then unlock the full question bank when you are ready to build a complete study routine.

The AWS Certified Generative AI Developer – Professional (AIP-C01) is a professional-level certification that validates a candidate's ability to effectively integrate foundation models (FMs) into applications and business workflows, and demonstrates practical knowledge of implementing generative AI solutions in production environments using AWS technologies. Covering five content domains—foundation model integration, implementation and integration, AI safety and governance, operational efficiency, and testing and troubleshooting—this certification assesses hands-on competency with AWS services such as Amazon Bedrock, Amazon SageMaker, and related AI/ML tooling. It is AWS's third Professional-level certification and was released in late 2025, reflecting the industry's growing demand for engineers who can deliver production-ready GenAI systems.

The credential specifically focuses on applied GenAI engineering skills such as designing retrieval-augmented generation (RAG) pipelines, building agentic AI solutions, applying prompt engineering techniques, managing vector stores and knowledge bases, and enforcing responsible AI and compliance practices. Notably out of scope are model development and training from scratch, advanced ML theory, and raw data engineering, making this certification distinctly focused on integration and production deployment rather than research or platform engineering.

This certification is designed for software and AI developers who build and deploy generative AI solutions on AWS or with open-source tooling. The target candidate typically holds a role such as AI/ML developer, cloud developer, or solutions engineer and is responsible for integrating foundation models into business applications, constructing agentic workflows, and ensuring those solutions are secure, cost-effective, and production-ready.

AWS recommends candidates have at least two years of experience building production-grade applications on AWS or with open-source technologies, general AI/ML or data engineering experience, and a minimum of one year of hands-on experience implementing generative AI solutions. Professionals transitioning into AI-focused development roles from software engineering or data engineering backgrounds are also well-positioned to pursue this certification.

There are no mandatory prerequisite certifications for the AIP-C01 exam. However, AWS recommends that candidates consider earning the AWS Certified AI Practitioner, AWS Certified Solutions Architect – Associate, AWS Certified Machine Learning Engineer – Associate, or AWS Certified Data Engineer – Associate before attempting this Professional-level exam, as those credentials build foundational knowledge that is assumed in the AIP-C01 content.

Candidates should bring working knowledge of AWS compute, storage, and networking services; AWS security best practices and identity and access management; deployment and infrastructure-as-code tools (e.g., AWS CloudFormation, AWS CDK); monitoring and observability services (e.g., Amazon CloudWatch); and AWS cost optimization principles. Familiarity with core GenAI concepts—foundation models, embeddings, vector databases, prompt engineering, and RAG architectures—is essential before attempting the exam.

The AIP-C01 exam consists of 75 total questions: 65 scored questions and 10 unscored pretest questions that are indistinguishable during the exam and do not affect the final score. AWS uses the unscored questions to evaluate them for future inclusion as scored items. The exam must be completed within 170 minutes and can be taken at a Pearson VUE testing center or via online proctored delivery. The exam is available in English and Japanese during the beta phase.

Question types include multiple choice (one correct answer out of four), multiple response (two or more correct answers that must all be selected to receive credit), ordering (arranging three to five steps in the correct sequence), and matching (correctly pairing three to seven prompt-response combinations). Scoring is compensatory—no per-domain passing threshold is required—and unanswered questions are scored as incorrect with no additional penalty for guessing. Results are reported as a scaled score from 100 to 1,000, with a minimum passing score of 750. The exam cost is $150 USD.

Holding the AWS Certified Generative AI Developer – Professional credential positions engineers for high-demand roles such as AI/ML developer, generative AI engineer, cloud application developer with AI specialization, and solutions architect focused on AI workloads. As organizations shift toward embedding AI capabilities into existing products rather than building standalone AI teams, developers who can demonstrate validated, production-grade GenAI integration skills on AWS gain a measurable competitive advantage in hiring and internal advancement. The Professional-level designation signals seniority beyond the AI Practitioner or Associate-tier credentials and aligns with engineering roles that carry greater autonomy and compensation.

The timing of this certification—launched in late 2025 alongside rapid enterprise adoption of foundation model APIs—reflects direct market demand. Professionals with proven GenAI deployment skills, particularly on the AWS ecosystem where Amazon Bedrock has become a leading enterprise FM platform, are well-positioned for salary premiums observed across cloud AI specializations. The Early Adopter badge awarded to the first 5,000 exam passers also provides an additional differentiator for early credential holders on professional profiles.